Wurmser, C. | Search bioRxiv

bioRxiv2018

A splice donor variant in CCDC189 is associated with asthenospermia in Nordic Red dairy cattle

BackgroundCattle populations are highly amenable to the genetic mapping of male reproductive traits because longitudinal data on ejaculate quality and dense microarray-derived genotypes are available for many artificial insemination bulls. Two young Nordic Red bulls delivered sperm with low progressive motility (i.e., asthenospermia) during a semen collection period of more than four months. The bulls were related through a common ancestor on both their paternal and maternal ancestry. Thus, a recessive mode of inheritance of asthenospermia was suspected. ResultsBoth bulls were genotyped at 54,001 SNPs using the Illumina BovineSNP50 Bead chip. A scan for autozygosity revealed that they were identical by descent for a 2.98 Mb segment located on bovine chromosome 25. This haplotype was not found in the homozygous state in 8,557 fertile bulls although five homozygous haplotype carriers were expected (P=0.018). Whole genome-sequencing uncovered that both asthenospermic bulls were homozygous for a mutation that disrupts a canonical 5 splice donor site of CCDC189 encoding the coiled-coil domain containing protein 189. Transcription analysis showed that the derived allele activates a cryptic splice site resulting in a frameshift and premature termination of translation. The mutated CCDC189 protein is truncated by more than 40%, thus lacking the flagellar C1a complex subunit C1a-32 that is supposed to modulate the physiological movement of the sperm flagella. The mutant allele occurs at a frequency of 2.5% in Nordic Red cattle. ConclusionsOur study in cattle uncovered that CCDC189 is required for physiological movement of sperm flagella thus enabling active progression of spermatozoa and fertilization. A direct gene test may be implemented to monitor the asthenospermia-associated allele and prevent the birth of homozygous bulls that are infertile. Our results have been integrated in the Online Mendelian Inheritance in Animals (OMIA) database (https://omia.org/OMIA002167/9913/).

genomics↗

bioRxiv2018

Accurate sequence variant genotyping in cattle using variation-aware genome graphs

BackgroundThe genotyping of sequence variants typically involves as a first step the alignment of sequencing reads to a linear reference genome. Because a linear reference genome represents only a small fraction of sequence variation within a species, reference allele bias may occur at highly polymorphic or diverged regions of the genome. Graph-based methods facilitate to compare sequencing reads to a variation-aware genome graph that incorporates non-redundant DNA sequences that segregate within a species. We compared sensitivity and accuracy of graph-based sequence variant genotyping using the Graphtyper software to two widely used methods, i.e., GATK and SAMtools, that rely on linear reference genomes using whole-genomes sequencing data of 49 Original Braunvieh cattle.\n\nResultsWe discovered 21,140,196, 20,262,913 and 20,668,459 polymorphic sites using GATK, Graphtyper, and SAMtools, respectively. Comparisons between sequence variant and microarray-derived genotypes showed that Graphtyper outperformed both GATK and SAMtools in terms of genotype concordance, non-reference sensitivity, and non-reference discrepancy. The sequence variant genotypes that were obtained using Graphtyper had the lowest number of mendelian inconsistencies for both SNPs and indels in nine sire-son pairs with sequence data. Genotype phasing and imputation using the Beagle software improved the quality of the sequence variant genotypes for all tools evaluated particularly for animals that have been sequenced at low coverage. Following imputation, the concordance between sequence- and microarray-derived genotypes was almost identical for the three methods evaluated, i.e., 99.39, 99.29, and 99.52 % for GATK, SAMtools, and Graphtyper, respectively. Graphtyper required considerably more computing resources than SAMtools but it required less than GATK.\n\nConclusionsSequence variant genotyping using Graphtyper is accurate, sensitive and computationally feasible in cattle. Graph-based methods enable sequence variant genotyping from variation-aware reference genomes that may incorporate cohort-specific sequence variants which is not possible with the current implementations of state-of-the-art methods that rely on linear reference genomes.

genomics↗